ICP error functional using point cloud geometry

Artyom Makovetskii; Sergei Voronin; Vitaly Kober; Aleksei Voronin

doi:10.1117/12.2633559

3 October 2022 ICP error functional using point cloud geometry

Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin

Proceedings Volume 12226, Applications of Digital Image Processing XLV; 122261G (2022) https://doi.org/10.1117/12.2633559
Event: SPIE Optical Engineering + Applications, 2022, San Diego, California, United States

Conference Poster

Abstract

Registration of point clouds in three-dimensional space is an important task in many areas of computer vision, including robotics and autonomous driving. The purpose of registration is to find a rigid geometric transformation to align two point clouds. The registration problem can be affected by noise and incomplete data availability (partiality). Iterative Closed Point (ICP) algorithm is a common method for solving the registration problem. Usually, the ICP algorithm monotonically reduces functional values, but owing to the problem of non-convexity, the algorithm often stops at suboptimal local minima. Thus, an important characteristic of the registration algorithm is its ability to avoid local minima. The probability of obtaining an acceptable transformation as a result of the ICP algorithm is a comparative criterion for different types of ICP algorithms and other types of registration algorithms. In this paper, we propose an ICP-type registration algorithm that uses a new type of error metric functional. The functional uses fine geometrical characteristics of the point cloud. Computer simulation results are provided to illustrate the performance of the proposed method.

Citation Download Citation

Artyom Makovetskii, Sergei Voronin, Vitaly Kober, and Aleksei Voronin "ICP error functional using point cloud geometry", Proc. SPIE 12226, Applications of Digital Image Processing XLV, 122261G (3 October 2022); https://doi.org/10.1117/12.2633559

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